Research graph
References from An AI-driven framework for intrusion detection and predictive threat modeling in UAV ecosystem. Local targets link to admitted publications; unresolved targets remain external evidence.
Autonomous vehicle security: hybrid threat modeling approach
10.1109/ojvt.2025.3580538 · 2025 · External reference
Supervised machine learning for real-time intrusion attack detection in connected and autonomous vehicles: a security paradigm shift
10.3390/informatics12010004 · 2025 · External reference
Predictive cybersecurity risk modeling in healthcare by leveraging AI and machine learning for proactive threat detection
10.9734/jerr/2025/v27i41463 · 2025 · External reference
Unresolved reference
External reference
Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure
10.1038/s41598-026-54260-2 · 2025 · External reference
FIR-GNN: a graph neural network using flow interaction relationships for intrusion detection of consumer electronics in smart home network
10.1109/tce.2025.3548798 · 2025 · External reference
A lightweight framework to secure IoT devices with limited resources in cloud environments
10.1038/s41598-025-09885-0 · 2025 · External reference
Intelligent cyber-attack detection for autonomous vehicles using advanced deep learning models
10.62762/tacs.2025.952297 · 2025 · External reference
Enhanced intrusion detection in drone networks: a cross-layer convolutional attention approach
10.3390/drones9010046 · 2025 · External reference
Towards securing UAV-assisted edge computing: a trust-based intrusion detection framework with multi-source feedback
2025 · External reference
Self-learning model fusion for network anomaly detection: a hybrid CNN-LSTM-transformer framework
10.1371/journal.pone.0332502 · 2025 · External reference
Network anomaly detection system using transformer neural networks and clustering techniques
2025 · External reference
Multi-scale transformers with contrastive learning for UAV anomaly detection
2025 · External reference
Applying vision transformers and large language models to anomaly detection for safer UAV landings
2025 · External reference
Securing UAV swarms with vision transformers: a byzantine-robust federated learning framework for cross-modal intrusion detection
10.3390/drones10020125 · 2026 · External reference
Unsupervised transformer-based anomaly detection for IoT networks
2025 · External reference
Agent-based dynamic thresholding for adaptive anomaly detection using reinforcement learning
10.1007/s00521-024-10536-0 · 2025 · External reference
An adaptive intrusion detection system for WSN using reinforcement learning and deep classification
10.1007/s13369-024-09769-x · 2025 · External reference
Enhancing cybersecurity in Internet of vehicles: a machine learning approach with explainable AI for real-time threat detection
2025 · External reference
Intrusion detection using metaheuristic optimization within iot/iiot systems and software of autonomous vehicles
10.1038/s41598-024-73932-5 · 2024 · External reference
UAVIDS-2025: A benchmark dataset for intrusion detection in UAV networks using machine learning techniques
2025 · External reference
Securing the future: AI-driven cybersecurity in the age of autonomous IoT
10.3389/friot.2025.1658273 · 2025 · External reference
Unresolved reference
2025 · External reference
A resource-efficient federated learning framework for intrusion detection in IoMT networks
10.1109/tce.2025.3544885 · 2025 · External reference
Lightweight fuzzy-driven intrusion detection for consumer life-tech applications
10.1109/tce.2025.3569886 · 2025 · External reference
Integrating embedded cyber-physical systems in smart energy for AI-enhanced real-time crowd monitoring and threat detection
10.1109/tce.2025.3576383 · 2025 · External reference
Multi-layered security architecture for iomt systems: integrating dynamic key management, decentralized storage, and dependable intrusion detection framework
10.1007/s13042-025-02628-7 · 2025 · External reference
Multi-attention DeepCRNN: an efficient and explainable intrusion detection framework for Internet of medical things environments
10.1007/s10115-025-02402-9 · 2025 · External reference
Transforming security in internet of medical things with advanced deep learning-based intrusion detection frameworks
10.1016/j.asoc.2025.113420 · 2025 · External reference
Cybersecurity-focused anomaly detection in connected autonomous vehicles using machine learning
2025 · External reference
Post-quantum protected federated learning with explainable and adaptive intelligence for smart city transportation
2026 · External reference
RHAD: a reinforced heterogeneous anomaly detector for robust industrial control system security
10.3390/electronics14122440 · 2025 · External reference
Enhancing vehicular network security, privacy, and trust through reinforcement learning: a comprehensive survey
10.1109/tits.2025.3612202 · 2025 · External reference
SMOTE: synthetic minority over-sampling technique
10.1613/jair.953 · 2002 · External reference
Real-time threat detection and AI-driven predictive security for consumer applications
10.1109/tce.2025.3554589 · 2025 · External reference
Modeling and optimizing IoT-driven autonomous vehicle transportation systems using intelligent multimedia sensors
10.1007/s11042-023-15563-y · 2025 · External reference
Unresolved reference
2025 · External reference
Towards proactive cloud security: a survey on ML and deep learning-based intrusion detection systems
2025 · External reference
Adaptive anomaly detection for identifying attacks in cyber-physical systems: a systematic literature review
10.1007/s10462-025-11292-w · 2025 · External reference
Agent-based dynamic thresholding for adaptive anomaly detection using reinforcement learning
10.1007/s00521-024-10536-0 · ExternalCitation · doi-reference
Multi-attention DeepCRNN: an efficient and explainable intrusion detection framework for Internet of medical things environments
10.1007/s10115-025-02402-9 · ExternalCitation · doi-reference
Adaptive anomaly detection for identifying attacks in cyber-physical systems: a systematic literature review
10.1007/s10462-025-11292-w · ExternalCitation · doi-reference
Modeling and optimizing IoT-driven autonomous vehicle transportation systems using intelligent multimedia sensors
10.1007/s11042-023-15563-y · ExternalCitation · doi-reference
Multi-layered security architecture for iomt systems: integrating dynamic key management, decentralized storage, and dependable intrusion detection framework
10.1007/s13042-025-02628-7 · ExternalCitation · doi-reference
An adaptive intrusion detection system for WSN using reinforcement learning and deep classification
10.1007/s13369-024-09769-x · ExternalCitation · doi-reference
Transforming security in internet of medical things with advanced deep learning-based intrusion detection frameworks
10.1016/j.asoc.2025.113420 · ExternalCitation · doi-reference
Intrusion detection using metaheuristic optimization within iot/iiot systems and software of autonomous vehicles
10.1038/s41598-024-73932-5 · ExternalCitation · doi-reference
A lightweight framework to secure IoT devices with limited resources in cloud environments
10.1038/s41598-025-09885-0 · ExternalCitation · doi-reference
Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure
10.1038/s41598-026-54260-2 · ExternalCitation · doi-reference
Autonomous vehicle security: hybrid threat modeling approach
10.1109/ojvt.2025.3580538 · ExternalCitation · doi-reference
A resource-efficient federated learning framework for intrusion detection in IoMT networks
10.1109/tce.2025.3544885 · ExternalCitation · doi-reference
FIR-GNN: a graph neural network using flow interaction relationships for intrusion detection of consumer electronics in smart home network
10.1109/tce.2025.3548798 · ExternalCitation · doi-reference
Real-time threat detection and AI-driven predictive security for consumer applications
10.1109/tce.2025.3554589 · ExternalCitation · doi-reference
Lightweight fuzzy-driven intrusion detection for consumer life-tech applications
10.1109/tce.2025.3569886 · ExternalCitation · doi-reference
Integrating embedded cyber-physical systems in smart energy for AI-enhanced real-time crowd monitoring and threat detection
10.1109/tce.2025.3576383 · ExternalCitation · doi-reference
Enhancing vehicular network security, privacy, and trust through reinforcement learning: a comprehensive survey
10.1109/tits.2025.3612202 · ExternalCitation · doi-reference
Self-learning model fusion for network anomaly detection: a hybrid CNN-LSTM-transformer framework
10.1371/journal.pone.0332502 · ExternalCitation · doi-reference
SMOTE: synthetic minority over-sampling technique
10.1613/jair.953 · ExternalCitation · doi-reference
Securing the future: AI-driven cybersecurity in the age of autonomous IoT
10.3389/friot.2025.1658273 · ExternalCitation · doi-reference
Securing UAV swarms with vision transformers: a byzantine-robust federated learning framework for cross-modal intrusion detection
10.3390/drones10020125 · ExternalCitation · doi-reference
Enhanced intrusion detection in drone networks: a cross-layer convolutional attention approach
10.3390/drones9010046 · ExternalCitation · doi-reference
RHAD: a reinforced heterogeneous anomaly detector for robust industrial control system security
10.3390/electronics14122440 · ExternalCitation · doi-reference
Supervised machine learning for real-time intrusion attack detection in connected and autonomous vehicles: a security paradigm shift
10.3390/informatics12010004 · ExternalCitation · doi-reference
Intelligent cyber-attack detection for autonomous vehicles using advanced deep learning models
10.62762/tacs.2025.952297 · ExternalCitation · doi-reference
Predictive cybersecurity risk modeling in healthcare by leveraging AI and machine learning for proactive threat detection
10.9734/jerr/2025/v27i41463 · ExternalCitation · doi-reference
